Hybrid ARQ retransmission method with reduced buffer size requirement and receiver therefor

ABSTRACT

A hybrid ARQ retransmission method in a communication system wherein data packets consisting of identical or partly identical modulation symbols encoded with a forward error correction (FEC) technique prior to transmission are retransmitted based on a repeat request and subsequently bit-level combined on the basis of soft-information values. The calculation of the soft-information values being input into an FEC decoder comprises the steps of calculating and buffering the soft-information values of the most significant bits (MSBs) of each (re)transmitted data packet; combining, for matching modulation symbols, the current soft-information values of the MSBs with the buffered soft-information values of at least one of the previous received transmitted packets; and calculating the soft information for at least some of the remaining bits (XSBs) from the combined soft information values of the MSBs.

[0001] The present invention relates to a hybrid ARQ retransmission method in a communication system. Further, the invention concerns a receiver embodied to carry out the method of the invention.

[0002] A common technique in communication systems with unreliable and time-varying channel conditions is to detect and correct errors based on automatic repeat request (ARQ) schemes together with a forward error correction (FEC) technique called hybrid ARQ (HARQ). If an error is detected within a packet by a commonly used cyclic redundancy check (CRC), the receiver of the communication system requests the transmitter to send additional information (data packet retransmission) to improve the probability of correctly decoding the erroneous packet.

[0003] A packet will be encoded with the FEC before transmission. Depending on the content of the retransmission and the way the bits are combined with previously transmitted information, S. Kallel, Analysis of a type II hybrid ARQ scheme with code combining, IEEE Transactions on Communications, Vol.38, No. 8, August 1990 and S. Kallel, R. Link, S. Bakhtiyari, Throughput performance of Memory ARQ schemes, IEEE Transactions on Vehicular Technology, Vol.48, No. 3, May 1999 define three different types of ARQ schemes:

[0004] Type I: The erroneous received packets are not discarded and a new copy of the same packet is retransmitted and decoded separately. There is no combining of earlier and later received versions of that packets.

[0005] Type II: The erroneous received packet(s) is(are) not discarded, but are combined with additional retransmissions for subsequent decoding. Retransmitted packets sometimes have higher coding rates (coding gain) and are combined at the receiver with the stored soft-information from previous transmission(s).

[0006] Type III: Is the same as Type II with the constraint each retransmitted packet is now self-decodable. This implies that the transmitted packet is decodable without the combination with previously transmitted packets. This is useful if some transmitted packets are damaged in such a way that almost no information is reusable.

[0007] This invention is related to Type II and Type III schemes, where the received (re)transmissions are combined. HARQ Type II and III schemes are obviously more intelligent and show a performance gain with respect to Type I, because they provide the ability to reuse information from previously received erroneous transmission packets. There exist basically three schemes of reusing the information of previously transmitted packets:

[0008] Soft-Combining

[0009] Code-Combining

[0010] Combination of Soft- and Code-Combining

[0011] Soft-Combining

[0012] Employing soft-combining the retransmission packets carry identical or partly identical information compared with the previously received information. In this case the multiple received packets are combined either by a symbol-by-symbol or by a bit-by-bit basis as for example disclosed in D. Chase, Code combining: A maximum-likelihood decoding approach for combining an arbitrary number of noisy packets, IEEE Trans. Commun., Vol. COM-33, pp. 385-393, May 1985 or B. A. Harvey and S. Wicker, Packet Combining Systems based on the Viterbi Decoder, IEEE Transactions on Communications, Vol. 42, No. 2/3/4, April 1994.

[0013] In case of employing symbol-level combining, the retransmitted packets have to carry identical modulation symbols to the previously transmitted erroneous packets. In this case the multiple received packets are combined at modulation symbol level. A common technique is the maximum ratio combining (MRC), also called average diversity combining (ADC), of the multiple received symbols, where after N transmissions the sum/average of the matching symbols is buffered.

[0014] In case of employing bit-level combining the retransmitted packets have to carry identical bits to the previously transmitted erroneous packets. Here, the multiple received packets are combined at bit level after demodulation. The bits can be either mapped in the same way onto the modulation symbols as in previous transmissions of the same packet or can be mapped differently. In case the mapping is the same as in previous transmissions also symbol-level combining can be applied. A common combining technique is the addition of calculated log-likelihood ratios (LLRs), especially if using so-called Turbo Codes for the FEC as known for example from C. Berrou, A. Glavieux, and P. Thitimajshima, Near Shannon Limit Error-Correcting Coding and Decoding: Turbo-Codes, Proc. ICC '93, Geneva, Switzerland, pp. 1064-1070, May 1993; S. Le Goff, A. Glavieux, C. Berrou, Turbo-Codes and High Spectral Efficiency Modulation, IEEE SUPERCOMM/ICC '94, Vol. 2, pp. 645-649, 1994; and A. Burr, Modulation and Coding for Wireless Communications, Pearson Education, Prentice Hall, ISBN 0-201-39857-5, 2001. Here, after N transmissions the sum of the LLRs of the matching bits is buffered.

[0015] For both mentioned soft-combing techniques—from a decoder point of view—the same FEC scheme (with constant code rate preferably) will be employed over all transmissions. Hence, the decoder does not need to know how many transmissions have been performed. It sees only the combined soft-information. In this scheme all transmitted packets will have to carry the same number of symbols or bits.

[0016] Code-Combining

[0017] Code-combining concatenates the received packets in order to generate a new code word (decreasing code rate with increasing number of transmission). Hence, the decoder has to be aware of the FEC scheme to apply at each retransmission instant. Code-combining offers a higher flexibility with respect to soft-combining, since the length of the retransmitted packets can be altered to adapt to channel conditions. However, this requires more signaling data to be transmitted with respect to soft-combining.

[0018] Combination of Soft- and Code-Combining

[0019] In case the retransmitted packets carry some symbols/bits identical to previously transmitted symbols/bits and some code-symbols/bits different from these ones, the identical code-symbols/bits are combined using soft-combing while the remaining code-symbols/bits will be combined using code-combining. Here, the signaling requirements will be similar to code-combining.

[0020] Employing a signal constellation for a 16 QAM modulation scheme according to FIG. 1 showing a Gray encoded signal constellation with a given bit-mapping order i₁q₁i₂q₂, the bits mapped onto the symbols differ significantly from each other in mean reliability in the first transmission of the packet. In more detail, bits i₁ and q₁ have a high mean reliability, as these bits are mapped to half spaces of the signal constellation diagram with the consequences that their reliability is independent from the fact of whether the bit transmits a one or a zero.

[0021] In contrast thereto, bits i₂ and q₂ have a low mean reliability, as their reliability depends on the fact of whether they transmit a one or a zero. For example, for bit i₂, ones are mapped to outer columns, whereas zeros are mapped to inner columns. Similarly, for bit q₂, ones are mapped to outer rows, whereas zeros are mapped to inner rows.

[0022] The combining of multiple received packets requires a buffering of the information from previously received packets. Depending on the possible combining methods, the modulation scheme and the packet size the buffer requirements per packet vary significantly. The total buffer-size requirement depends also on the higher layer ARQ protocol, which is usually a multiple of the buffer-size requirement per packet. For simplification pure soft-combining is described in this section. Same applies to the soft-combined buffering part for the combination of soft- and code-combining.

[0023] In case of symbol-level combining the soft-information according to the received modulation symbol has to be stored (complex value). This leads to a buffer-size requirement per packet B_(SC), which can be approximately calculated as follows: $\begin{matrix} {B_{SC} = {\frac{2{Nb}_{S}}{\log_{2}(M)} + b_{K}}} & (1) \end{matrix}$

[0024] with N number of encoded bits per packet log₂(M) number of encoded bits mapped onto one modulation symbol 2b_(S) bit-depth: Number of bits for representing one modulation symbol in buffer (I- and Q-part) b_(K) bit-depth: Number of bits for representing the sum of the received power (all signal to noise ratios) by all packets;

[0025] where K is an optionally stored measure for the channel quality. If it is not stored, b_(K)=0.

[0026] In case of bit-level combining the soft-information of the bits have to be stored. This leads to a buffer-size requirement per packet B_(BC), which is independent from the number of encoded bits mapped onto a modulation symbol:

B _(BC) =Nb _(B)  (2)

[0027] with N number of bits per packet b_(B) bit-depth: Number of bit representing one soft-information (e.g. LLR) in buffer

[0028] The ratio of the required buffer-size for symbol-combining to bit-combining can be calculated by use of equations $\begin{matrix} {\frac{B_{SC}}{B_{BC}} = {\frac{2b_{s}}{{\log_{2}(M)}b_{B}} + \frac{b_{K}}{\underset{\underset{{{{small}\quad {compared}\quad {to}\quad 1},{addend}}{{since}\quad N\quad {is}\quad {usually}\quad {large}\quad {and}}{{{usually}\quad {b_{K}/b_{B}}} \leq 1}}{}}{{Nb}_{B}}}}} & (3) \end{matrix}$

[0029] Usually, the ratio of the bit-depths b_(B)/b_(S) is between ⅔ and 1, which makes symbol-level combining requiring less buffer than bit-level combining from log₂(A)>2. In case the performance for both combining methods is equal or close to equal, for complexity reasons then at the receiver for higher order modulation schemes (log₂(M)>2) usually symbol-level combining is preferred.

[0030] As it was shown in the previous section—in case of high-order modulation—the soft-combining at symbol-level has lower buffer-size requirements per packet at the receiver compared to bit-level combining. This leads to the fact that symbol-level combining is mostly preferred over bit-level combining. However, in terms of receiver design, implementation efficiency and buffer management it can be beneficial to perform bit-level combining (buffering), especially if the FEC decoder works on bit-level (e.g. Turbo decoder).

[0031] The object of the invention is to provide a hybrid ARQ retransmission method and a corresponding receiver with lowered buffer-size requirements for HARQ bit-level combining.

[0032] This object is solved by a hybrid ARQ transmission method as defined by claim 1. Preferred embodiments of the retransmission method are subject to various dependent claims. Further, the object is solved by a corresponding receiver as recited in claim 11.

[0033] With respect to the prior art bit-level combining methods, where the soft information of all bits has to be buffered, according to the invention, the retransmission method only requires the buffering of the soft information of the most significant bits MSBs which leads to a significantly lowered buffer-size requirement. With respect to symbol-level combining, the advantages of bit-level combining in terms of receiver design, implementation, efficiency and buffer management remain at equal or even lower buffer-size requirements. The invention will be more readily understood from the following detailed description with reference to the accompanying drawings shown:

[0034]FIG. 1: a Gray encoded signal constellation for 16-QAM;

[0035]FIG. 2: a Gray encoded signal constellation for 64-QAM; and

[0036]FIG. 3: relevant parts of a receiver of a communication system, in which the present invention is employed.

[0037] With reference to FIG. 3, those parts of a communications receiver which are concerned with the subject matter of the present invention are illustrated.

[0038] A demodulator 100 receives complex modulation symbols S, which have been transmitted by a transmitter of a communication system. For the first transmission, for all modulation symbols the LLRs (MSBs and LSBs) are calculated.

[0039] In accordance with an automatic repeat request scheme, the receiver requests the transmitter to send additional transmissions of erroneously received data packets. For each received modulation symbol S, soft information, in the preferred embodiment of log-likelihood-ratios (LLRs), is calculated in a corresponding calculator 150 for the high reliable, most significant bits (MSBs) as well for the real part (I-part) as for the imaginary part (Q-part) and subsequently stored in a buffer 160.

[0040] In a subsequent combiner 170, the LLRs of the actual received data packet and the LLRs from previously received data packets which are stored in the buffer 160 are combined for each matching modulation symbol. From this combined soft-information (accounting for all received transmissions), the LLRs for the remaining bits up to the least significant bits (LSBs) are calculated in an LLRs calculator 180 and input together with the LLRs of the MSB calculator 150 into a decoder 200. The decoder outputs its infobits to an error checker 300 for detecting and possibly correcting errors. The decoder preferably applies a forward error correction scheme employing the received soft information. Such decoders can be implemented as described, for example, in C. Heergard, S. B. Wicker, Turbo Coding, Kluwer Academic Publishers, ISBN 0-7923-8378-8, 1999 or F. Xiong, Digital Modulation Techniques, Artech House Publichers, ISBN 0-89006-970-8, 2000.

[0041] All components described above are in its detailed implementation known to a skilled person in the art. A detailed description has therefore been omitted for simplicity.

[0042] The advantage of the receiver design proposed above is that the required buffer-size is significantly reduced as only the MSBs are stored. This reduces the receiver complexity and allows easier calculation and buffer management because the HARQ information is buffered at bit level and the FEC decoder preferably also works at bit level.

[0043] Next, the method of the invention will be described in more detail with linearly approximated LLRs as soft-information at the receiver.

[0044] Linear Approximation for LLR Calculation (Single Transmission)

[0045] Before describing the rule for how to calculate the LLRs after multiple transmissions, first a description of the approximation of the LLR in the single transmission case is given. The calculations are performed for 16-QAM and 64-QAM, but can easily extended to higher order M-QAM schemes. The indices for the coordinates of the signal constellation points (x_(i), y_(i)) and the considered Gray-mappings for LLR calculations are according to FIG. 1 and FIG. 2. For simplicity the following description is made for the i-bits only. The procedure for the q-bits is analogue, where Re{r} has to be replaced by Im{r} and x_(i) has to be replaced by y_(i).

[0046] MSB Approximation—i₁ (q₁)

[0047] The LLR for the MSBs is approximated as follows: $\begin{matrix} {{{LLR}\left( i_{1} \right)} = {\frac{P\left( {i_{1} = {1\left. r \right)}} \right.}{P\left( {i_{1} = {0\left. r \right)}} \right.} \approx {{- 4}A_{1}{Kx}_{0}{Re}\left\{ r \right.}}} & (4) \end{matrix}$

[0048] with $K = {10^{\frac{E_{s}/N_{0}}{10}}:}$

[0049] K represents a measure for the channel quality

[0050] A₁∈[0.5;2]: Correction Factor (preferred A₁=1)

[0051] r: Received (Equalized) Modulation Symbol

[0052] K is preferably calculated as indicated above, where E_(s)/N₀ represents the signal to noise ratio in the channel

[0053] Approximation—i₂ (q₂)

[0054] The LLRs for i₂ (q₂) can be approximated as follows (in case of 16-QAM i₂ and q₂ are the LSBs): $\begin{matrix} {{{LLR}\left( i_{2} \right)} = {\frac{P\left( {i_{2} = {1\left. r \right)}} \right.}{P\left( {i_{2} = {0\left. r \right)}} \right.} \approx {{2A_{2}{K\left( {x_{m + 1} - x_{m}} \right)}{{{Re}\left\{ r \right\}}}} + {A_{3}{K\left( {x_{m}^{2} - x_{m + 1}^{2}} \right)}}}}} & (5) \end{matrix}$

[0055] and with equation LLR(i₂) can be expressed as a function of LLR(i₁) $\begin{matrix} {{{LLR}\left( i_{2} \right)} \approx {{\frac{A_{2}\left( {x_{m + 1} - x_{m}} \right)}{2A_{1}x_{0}}{{{LLR}\left( i_{1} \right)}}} + {A_{3}{K\left( {x_{m}^{2} - x_{m + 1}^{2}} \right)}}}} & (6) \end{matrix}$

[0056] with $m = {\frac{\sqrt{M}}{4} - 1}$

$K = 10^{\frac{E_{s}/N_{0}}{10}}$

[0057] A₂∈[0.5;2]: Correction Factor (preferred A₂=1)

[0058] A₃∈[0.5;2]: Correction Factor (preferred A₃=1)

[0059] r: Received (Equalized) Modulation Symbol

[0060] In case of equally spaced constellation points (x₁=3x₀) equation (6) generally simplifies to $\begin{matrix} {{{LLR}\left( i_{2} \right)} \approx {{\frac{A_{2}}{A_{1}}{{{LLR}\left( i_{1} \right)}}} + {A_{3}{K\left( {x_{m}^{2} - x_{m + 1}^{2}} \right)}}}} & (7) \end{matrix}$

[0061] Approximation—i₃ (q₃)

[0062] In case of 64-QAM the LLRs for i₃ (q₃) can be approximated as follows (i₃ and q₃ are then the LSBs): $\begin{matrix} {{{LLR}\left( i_{3} \right)} = {\frac{P\left( {i_{3} = {1\left. r \right)}} \right.}{P\left( {i_{3} = {0\left. r \right)}} \right.} \approx \left\{ \begin{matrix} {2A_{4}{K\left( {x_{m} - x_{m + 1}} \right)}{{{Re}\left\{ r \right\}}}A_{5}{K\left( {x_{m + 1}^{2} - x_{m}^{2}} \right)}} \\ {{{for}\quad {{{Re}\left\{ r \right\}}}} < \frac{x_{\sqrt{M}/4} + x_{{\sqrt{M}/4} - 1}}{2}} \\ {{2A_{6}{K\left( {x_{l} - x_{l - 1}} \right)}{{{Re}\left\{ r \right\}}}} + {A_{7}{K\left( {x_{l - 1}^{2} - x_{l}^{2}} \right)}}} \\ {otherwise} \end{matrix} \right.}} & (8) \end{matrix}$

[0063] and with equation (6) LLR(i₃) can be expressed as a function of LLR(i₁) $\begin{matrix} {{{LLR}\left( i_{3} \right)} \approx \left\{ {{\begin{matrix} \left. \frac{A_{4}\left( {x_{m} - x_{m + 1}} \right)}{2A_{1}x_{0}} \middle| {{LLR}\left( i_{1} \right)} \middle| {{+ A_{5}}{K\left( x_{m + 1}^{2} \right.}} \right. \\ {\left. {for}\quad \middle| \quad {{Re}\left\{ r \right\}} \middle| {< \frac{x_{\sqrt{M}/4} + x_{{\sqrt{M}/4} - 1}}{2}} \right.\quad} \\ \left. {2A_{6}{K\left( {x_{1} - x_{l - 1}} \right)}} \middle| {{Re}\left\{ r \right\}} \middle| {{+ A_{7}}{K\left( {x_{l - 1}^{2} - x_{l}^{2}} \right)}} \right. \\ {otherwise} \end{matrix}{with}m} = {{\frac{\sqrt{M}}{8} - {1l}} = {{\frac{\sqrt{M}}{2} - 1 - {mK}} = 10^{\frac{E_{s}/N_{0}}{10}}}}} \right.} & (9) \end{matrix}$

[0064] A₄∈[0.5;2]: Correction Factor (preferred A₄=1)

[0065] A₅∈[0.5;2]: Correction Factor (preferred A₅=1)

[0066] A₆∈[0.5;2]: Correction Factor (preferred A₆=1)

[0067] A₇∈[0.5;2]: Correction Factor (preferred A₇=1)

[0068] r: Received (Equalized) Modulation Symbol

[0069] In case of equally spaced constellation points equation (9) simplifies for 64-QAM to $\begin{matrix} \left. {{{LLR}\left( i_{3} \right)} \approx} \middle| \frac{A_{4}}{A_{1}} \middle| {{LLR}\left( i_{1} \right)} \middle| {{- 16}{Kx}_{0}^{2}} \middle| {{- 8}A_{5}{Kx}_{0}^{2}} \right. & (10) \end{matrix}$

[0070] LLR Calculation After N Transmissions

[0071] The calculation of the LLR after n transmissions is shown for the i-bits only. The procedure for the q-bits is analogue, where Re{r^((n))} has to be replaced by Im{r^((n))} and x_(i) has to be replaced by y_(i), where n indicates the n-th transmission.

[0072] MSB Calculation—i₁ (q₁)

[0073] With equation (4) the total LLR for i₁ (q₁) after the n-th transmission can be calculated as the sum of all LLRs calculated from n transmissions. In the receiver this leads to a sum of the calculated LLR of the currently received n-th transmission and the buffered sum of LLRs of previously received transmissions: $\begin{matrix} {{{{LLR}_{tot}^{(n)}\left( i_{1} \right)} \approx {{{- 4}A_{1}K^{(n)}{x_{0} \cdot {Re}}\left\{ r^{(n)} \right\}} + \underset{\underset{\underset{{{from}\quad {previous}\quad {transmissions}}\quad}{{buffered}\quad {{informatio}{({LLR})}}}}{}}{{LLR}_{tot}^{({n - 1})}\left( i_{1} \right)}}}{With}{{{{LLR}_{tot}^{({n - 1})}\left( i_{1} \right)} \approx {\sum\limits_{p = 1}^{n - 1}\quad {{LLR}^{(p)}\left( i_{1} \right)}}}:}} & (11) \end{matrix}$

[0074] Buffered info (LLR) at receiver $K^{(n)} = 10^{\frac{{({E_{s}/N_{0}})}^{(n)}}{10}}$

[0075] A₁∈[0.5;2]: Correction Factor (preferred A₁=1)

[0076] r^((n)): Received (Equalized) Modulation Symbol at n-th Transmission

[0077] Calculation—i₂ (q₂)

[0078] With equations and the total LLR for i₂ (q₂) after the n-th transmission can be expressed as a function of the total LLR i₁ (q₁): $\begin{matrix} \begin{matrix} \left. {{{LLR}_{tot}^{(n)}\left( i_{2} \right)} \approx {{- \frac{A_{2}\left( {x_{m} - x_{m + 1}} \right)}{2A_{1}x_{0}}}\sum\limits_{p = 1}^{n}}}\quad \middle| {{LLR}^{(p)}\left( i_{1} \right)} \middle| {{+ {A_{3}\left( {x_{m}^{2} - x_{m + 1}^{2}} \right)}}K^{(p)}} \right. \\ \left. {\approx {- \frac{A_{2}\left( {x_{m} - x_{m + 1}} \right)}{2A_{1}x_{0}}}} \middle| {{LLR}_{tot}^{(n)}\left( i_{1} \right)} \middle| {{+ {A_{3}\left( {x_{m}^{2} - x_{m + 1}^{2}} \right)}}{\sum\limits_{p = 1}^{n}\quad K^{(p)}}} \right. \\ {{\approx {{{- \frac{A_{2}\left( {x_{m} - x_{m + 1}} \right)}{2A_{1}x_{0}}}\underset{\underset{\underset{{from}\quad i_{1}\quad {calculation}}{{buffered}\quad {total}\quad {LLR}}}{}}{\left| {{LLR}_{tot}^{(n)}\left( i_{1} \right)} \right|}}\quad + {{A_{3}\left( {x_{m}^{2} - x_{m + 1}^{2}} \right)}\underset{\underset{\underset{{received}\quad {power}}{{buffered}\quad {total}}}{}}{K_{tot}^{(n)}}}}}\quad} \\ {with} \\ {m = {\frac{\sqrt{M}}{4} - 1}} \\ {K_{tot}^{(n)} = {\sum\limits_{p = 1}^{n}\quad K^{(p)}}} \end{matrix} & (12) \end{matrix}$

[0079] A₂∈[0.5;2]: Correction Factor (preferred A₂=1)

[0080] A₃∈[0.5;2]: Correction Factor (preferred A₃=1)

[0081] In case of equally spaced constellation points equation (12) generally simplifies to $\begin{matrix} \left. {{{LLR}_{tot}^{(n)}\left( i_{2} \right)} \approx \frac{A_{2}}{A_{1}}} \middle| {{LLR}_{tot}^{(n)}\left( i_{1} \right)} \middle| {{+ {A_{3}\left( {x_{m}^{2} - x_{m + 1}^{2}} \right)}}K_{tot}^{(n)}} \right. & (13) \end{matrix}$

[0082] Calculation—i₃(q₃)

[0083] Analogous to the total LLR for i₂ (q₂) the total LLR for i₃ (q₃) after the n-th transmission can be calculated by use of equations (4), (8) and (9) and as follows: $\begin{matrix} {{{LLR}_{tot}^{(n)}\left( i_{3} \right)} \approx \left\{ {{\begin{matrix} {{\frac{A_{4}\left( {x_{m} - x_{m + 1}} \right)}{2A_{1}x_{0}}\underset{\underset{\underset{{from}{\quad \quad}i_{1}\quad {calculation}}{{buffered}\quad {total}\quad {LLR}}}{}}{\left| {{LLR}_{tot}^{(n)}\left( i_{1} \right)} \right|}} + {{A_{5}\left( {x_{m + 1}^{2} - x_{m}^{2}} \right)}\underset{\underset{\underset{{received}\quad {power}}{{buffered}\quad {total}}}{}}{K_{tot}^{(n)}}}} \\ \left. {for}\quad \middle| {{LLR}\left( i_{1} \right)} \middle| {< {2A_{1}K_{tot}^{(n)}{x_{0}\left( {x_{\frac{\sqrt{M}}{4}} + x_{\frac{\sqrt{M}}{4 - 1}}} \right)}}} \right. \\ {{\frac{A_{6}\left( {x_{1} - x_{l - 1}} \right)}{2A_{1}x_{0}}\underset{\underset{\underset{{from}\quad i_{1}\quad {calculation}}{{buffered}\quad {total}\quad {LLR}}}{}}{\left| {{LLR}_{tot}^{(n)}\left( i_{1} \right)} \right|}} + {{A_{7}\left( {x_{l - 1}^{2} - x_{l}^{2}} \right)}\underset{\underset{\underset{{received}\quad {power}}{{buffered}{\quad \quad}{total}}}{}}{K_{tot}^{(n)}}}} \\ {otherwise} \end{matrix}{with}m} = {{\frac{\sqrt{M}}{8} - {1l}} = {{\frac{\sqrt{M}}{8} - 1 - {mK_{tot}^{(n)}}} = {\sum\limits_{p = 1}^{n}\quad K^{(p)}}}}} \right.} & (14) \end{matrix}$

[0084] A₄∈[0.5;2]: Correction Factor (preferred A₄=1)

[0085] A₅∈[0.5;2]: Correction Factor (preferred A₅=1)

[0086] A₆∈[0.5;2]: Correction Factor (preferred A₆=1)

[0087] A₇∈[0.5;2]: Correction Factor (preferred A₇=1)

[0088] In case of equally spaced constellation points equation (14) simplifies for 64-QAM to $\begin{matrix} \left. {{{LLR}_{tot}^{(n)}\left( i_{3} \right)} \approx} \middle| \frac{A_{4}}{A_{1}} \middle| {{LLR}_{tot}^{(n)}\left( i_{1} \right)} \middle| {{- 16}K_{tot}^{(n)}x_{0}^{2}} \middle| {{- 8}A_{5}K_{tot}^{(n)}x_{0}^{2}} \right. & (15) \end{matrix}$

[0089] As stated earlier only the LLRs of the MSBs (I- and Q-parts) per modulation symbol and the sum of the total received power over all packets has to be stored. This leads for the proposed method to the following equation for the buffer-size B_(PM): $\begin{matrix} {B_{PM} = {\frac{2{Nb}_{B}}{\log_{2}(M)} + b_{K}}} & (16) \end{matrix}$

[0090] with M M-QAM N number of encoded bits per packet b_(B) bit-depth for representing one soft-information (e.g. LLR) in buffer b_(K) bit-depth for representing the sum of the received power by all packets

[0091] The ratio of the required buffer-size to the buffer-size for symbol-level combining as described above yields for any M-QAM scheme: $\begin{matrix} {\frac{B_{PM}}{B_{SC}} = {\frac{\frac{2{Nb}_{B}}{\log_{2}(M)} + b_{K}}{\frac{2{Nb}_{S}}{\log_{2}(M)} + b_{K}} = \frac{{2{Nb}_{B}} + {b_{K}{\log_{2}(M)}}}{{2{Nb}_{S}} + {b_{K}{\log_{2}(M)}}}}} & (17) \end{matrix}$

[0092] If N (bits per packet) is sufficiently large equation (17) becomes approximately: $\begin{matrix} {\frac{B_{PM}}{B_{SC}} \approx \frac{b_{B}}{b_{S}}} & (18) \end{matrix}$

[0093] If it is assumed that the required bit-depth b_(B) for buffering a LLR is smaller than the bit-depth b_(S) for buffering one part of a complex modulation symbol, a reduction in buffer-size compared to symbol-level buffering can be achieved (e.g. reduction of 25% for b_(B)=6 and b_(S)=8).

[0094] The ratio of the required buffer-size for the inventive method to the buffer-size for conventional bit-level combining yields: $\begin{matrix} {\frac{B_{PM}}{B_{SC}} = {\frac{\frac{2{Nb}_{B}}{\log_{2}(M)} + b_{K}}{{Nb}_{B}} = {\frac{2}{\log_{2}(M)} + \frac{b_{K}}{{Nb}_{B}}}}} & (19) \end{matrix}$

[0095] If N (bits per packet) is sufficiently large equation (19) becomes approximately: $\begin{matrix} {\frac{B_{PM}}{B_{SC}} \approx \frac{2}{\log_{2}(M)}} & (20) \end{matrix}$

[0096] This corresponds to a buffer-size reduction compared to conventional bit-level combining as shown in Table 1: TABLE 1 Modulation Scheme Buffer-Size Reduction QPSK  0% 16-QAM 50% 64-QAM 67% 256-QAM  75%

[0097] As demonstrated above, the inventive method results in some advantages in terms of calculation complexity and buffer management. The performance for using the proposed bit-level combining method compared to the symbol-combining method is similar. In case of using linearly approximated LLRs as described herein for the proposed bit-combining and using also linearly approximated LLRs after symbol-combining, the performance is exactly the same.

[0098] The skilled person is immediately aware that other than the above described 16-QAM and 64-QAM, any other M-QAM or M-PAM (pulse amplitude modulation) for log₂(M)>1 Gray-mappings are applicable to the method of the present invention and the respective equations can be derived accordingly. As mentioned earlier, the method of the present invention is also applicable to HARQ schemes employing the retransmission of a subset of previously transmitted symbols. The derived calculation for the LLRs and the buffer size is valid for the symbols which are retransmitted and combined.

[0099] The soft-information, which can be used in connection with the present invention might be any soft-metric describing a (preferably logarithmic) measure of the probability of the corresponding bit to be a 1 or a 0. The soft information as described above are log-likelihood ratios. However, the soft-information might be a soft-metric of the respective bit calculated as a linear equation from the I and Q-components of the received modulation symbol.

[0100] The above described combining step might be a simple addition of the LLRs or soft-information and the respective calculation thereof for the remaining bits might simply be a linear function in the style of

LLR _(XSB) =a·LLR _(MSB) +b or LLR_(XSB) =a·|LLR _(MSB) |+b

[0101] where the function is possibly defined in sections. 

1. A hybrid ARQ retransmission method in a communication system, wherein data packets consisting of identical or partly identical modulation symbols encoded with a forward error correction (FEC) technique prior to transmission are retransmitted based on a repeat request and subsequently bit-level combined on the basis of soft-information values which are input into an FEC decoder comprising the steps of: calculating and buffering the soft-information values of the most significant bits (MSBs) of each (re)transmitted data packet, combining, for matching modulation symbols, the current soft-information values of the MSBs with the buffered soft-information values of at least one of the previous received transmitted packets, and calculating the soft information for at least some of the remaining bits (XSBs) from the combined soft information values of the (MSBs).
 2. The retransmission method according to claim 1, wherein the soft-information value is a logarithmic measure of the probability of the corresponding bits to be a 1 or a
 0. 3. The retransmission method according to claim 1, wherein the soft-information value is a log-likelihood ratio (LLR).
 4. The retransmission method according to claim 1, wherein the soft-information value is a soft metric of the corresponding bit calculated as a linear equation from at least one of the I and Q component of the received modulation symbol.
 5. The retransmission method according to claim 1, wherein the step of combining comprises an addition of the soft-information values.
 6. The retransmission method according to claim 3, wherein the step of calculating the remaining bits (XSBs) comprises applying a linear function LLR _(XSB) =a·LLR _(MSB) +b or LLR _(XSB) =a·|LLR _(MSB) |+b where the function is possibly defined in sections.
 7. The retransmission method according to claim 1, wherein the modulation scheme is M-QAM (log₂(M)>2) with Gray mappings.
 8. The retransmission method according to claim 1, wherein the modulation scheme is M-PAM (log₂(M)>1) with Gray mappings.
 9. The retransmission method according to claim 1, comprising the further step of buffering a measure for the channel quality, preferably the sum of an estimated and/or signaled signal-to-noise ratio E_(s)/N₀ overall transmissions.
 10. The method according to claim 1, wherein old remaining bits up to the least significant bits (LSBs) are calculated from the combined soft-information values.
 11. A receiver for a hybrid ARQ retransmission method in a communication system, comprising: a demodulator for receiving data packets consisting of identical or partly identical modulation symbols, a calculator for calculating soft-information values of the most significant bits (MSBs) of each (re)transmitted data packet, a buffer for storing the calculated soft-information values, a combiner for combining current soft-information values of the MSBs with the buffered soft-information values of at least one of the previous received data packets, and a calculator for calculating the soft-information values for at least some of the remaining bits (XSBs) from the combined soft-information values of the MSBs.
 12. A receiver according to claim 11, wherein the soft-information value calculator is a log-likelihood ratio (LLR) calculator.
 13. The receiver according to claim 11, further comprising a decoder for receiving the soft-information values from the calculator and the calculator for the remaining bits (XSBs). 